The invention relates generally to sampled distance fields, and more particularly to adaptively resampling distance fields to obtain a more precise graphics model.
Designing realistic digitized models is a major challenge for the animation industry, particularly when the models represent characters such as peoplexe2x80x94real or imagined, animals, and cartoon characters. Animation artists generally employ two production methods, alone or in combination. In one method, maquettes are sculpted from a traditional medium like clay and then digitized. In another method, the models are constructed using one of several commercial or custom computerized modeling systems, such as MAYA, SoftImage, 3DStudioMax, FormZ, and Houdini.
Clay is the medium of choice for most animation artists because it is expressive, and working with clay is intuitive. It is difficult to improve on clay as the ideal modeling medium. A standard approach for designing clay-based digital models involves sculpting a clay maquette and digitizing or scanning the maquette to generate the digital model. There is a plethora of systems for scanning objects and generating surface models from the scanned data.
However, sculpting with clay and then digitizing the clay maquette has several limitations for digital animation. Much detail can be lost in the digitizing process because scanners and digitizers have inherent limitations in resolution, are unable to digitize occluded or hard-to-reach surfaces, and are subject to noise. Thus, some of the advantages of clay are lost in the scanning process. Furthermore, long-term storage of the clay models is difficult. It is important to note, however, that scanned models can provide good first order approximations to the geometry of the clay maquettes that can then be enhanced by a computer-based modeling system. Hence, it is important that any modeling system does accept scanned data as input.
Most prior art computerized modeling systems typically use polygons, non-uniform rational B-splines (NURBS), or other subdivisions of planar surfaces to represent the shape of a model. However, all three representations have limitations.
Polygon models require a large number of vertices to represent detailed surfaces, particularly when the surfaces are highly curved, textured, or include sharp edges. This makes model generation and editing with polygons cumbersome and time consuming. Because NURBS are topologically restricted, they must be pieced together to form complex shapes. This presents numerous technical and interface challenges, see DeRose et al., xe2x80x9cSubdivision surfaces in character animation,xe2x80x9d Proc. SIGGRAPH ""98, pp. 85-94, 1998. While subdivision of planar surfaces does not suffer from the same topological restrictions as NURBS, controlling shape changes, and adding fine detail during editing are difficult. As another problem, all of these modeling techniques are only surface representationsxe2x80x94the models are nothing more than hollow shells and nothing is known about interior portions.
Even worse, sculpting of surface representations can lead to models that are not xe2x80x9cwatertight.xe2x80x9d For example, seams where different resolution NURBS are joined can separate to form annoying cracks and holes. This means that the sculpted models have to be carefully inspected and edited before a watertight finished product is produced. Watertight models are important for several applications such as rapid prototyping technologies including stereo lithography.
All computerized modeling systems usually perform editing by manipulating control vertices. This requires significant skill and patience, as well as foresight and careful planning to ensure that the models have enough control vertices where detail is desired. For these reasons, computerized modeling systems do not rival the intuitive and expressive nature of clay.
To make the manipulation more intuitive, most modeling systems allow the user to interact with groups of control vertices using a computer implemented (digital) sculpting tool. For example, in MAYA Artisan, NURBS models are modified via a brush tool that manipulates groups of control vertices. Operations for pushing, pulling, smoothing, and erasing the surface are well known, and the brush tool can affect control vertices in a region of diminishing influence around its center, resulting in a softening of the sculpted shape. The amount of detail in the sculpted surface depends on the number of control vertices in the region of the sculpting tool. Finer control requires more subdivision of the NURBS surface, resulting in a less responsive system and a larger model. Often, mesh subdivision is user controlled and preset. It does not adapt to tool selection, or the detail of the sculpted surface. Hence, achieving fine detail in desired regions without excessive subdivision of the surface in other regions requires significant foresight and planning.
SoftImage provides a sculpting interface, called xe2x80x9cMeta-Clay,xe2x80x9d that is similar to the xe2x80x9cmetaballsxe2x80x9d technology as described by Wyvill et al. in xe2x80x9cAnimating soft objects,xe2x80x9d the Visual Computer, 2(4):235-242, 1986. Meta-Clay is a density based representation for modeling organic, sculpted objects. This representation produces blobby shapes, and does not represent edges, corners, or fine detail.
Sculpting of parametric models are described by Fowler, xe2x80x9cGeometric manipulation of tensor product surfaces,xe2x80x9d Proc. of the 1992 Symposium on Interactive 3D Graphics, pp. 101-108, 1992, Khodakovsky et al. xe2x80x9cFine Level Feature Editing for Subdivision Surfaces,xe2x80x9d ACM Solid Modeling Symposium, 1999, and Terzopoulos et al. xe2x80x9cDynamic NURBS with geometric constraints for interactive sculpting,xe2x80x9d ACM Transactions On Graphics, 13(2), pp. 103-136, 1994. However, each of these suffers from some of the limitations described above, and none attain sculpted results of the quality required for the animation industry.
To address the problems of polygon, NURBS, and other surface subdivision representations, volumetric data structures can be used. These data structures can be generated parametrically or by sampling techniques using, for example, laser or other ranging techniques, or scanners that penetrate the object to be modeled. Volumetric data can represent both the exterior and interior portions of models. The volumetric data are then sculpted by applying digital sculpting tools. The tools modify sample values near where the sculpting tool interacts with the volume. For these reasons, sampled volumes hold more promise as a data structure for digital clay.
FreeForm is a commercial system for sculpting volumetric models. FreeForm includes a three degree-of-freedom haptic input device which uses force feedback to provide the user with a sense of touch when sculpting. Models are represented as regularly sampled intensity values. This greatly limits the amount of detail that can be achieved, and requires excessive amounts of memory. For example, a minimum system requires 512 MB of random access memory (RAM). Intensity values can be low-pass filtered to reduce aliasing artifacts in the sculpted models, resulting in smoothed edges and rounded corners typical in volumetric sculpting systems.
To take advantage of standard hardware rendering engines, volumetric models can be converted to polygon models using a method such as described by Lorensen et al. in xe2x80x9cMarching Cubes: A High Resolution 3D Surface Construction Algorithm,xe2x80x9d Proc. SIGGRAPH ""87, pp.163-169, 1987. However, with large volume sizes, Marching Cubes produces an excessive number of triangles, leading to memory overload and bottlenecks in the graphics rendering pipeline which limit interactivity.
There are a number of publications that describe volume-based sculpting systems including Avila et al. xe2x80x9cA haptic interaction method for volume visualization,xe2x80x9d Proc. IEEE Visualization""96, pp. 197-204, 1996, Baerentzen, xe2x80x9cOctree-based volume sculpting Proc. Late Breaking Hot Topics,xe2x80x9d IEEE Visualization""98, pp. 9-12, 1998, Galyean et al. xe2x80x9cSculpting: An Interactive Volumetric Modeling Technique,xe2x80x9d Proc. SIGGRAPH ""91, pp. 267-274, 1991, and Wang et al. xe2x80x9cVolume sculpting,xe2x80x9d 1995 Symposium on Interactive 3D Graphics, ACM SIGGRAPH, pp. 151-156, 1995.
However, each of these systems suffers from some of the limitations described above, such as large memory requirements, a fixed resolution determined by the volume size, and soft edges. As a result, such systems are of little use to the high-end digital animation industry.
State of the art digital studios, such as Industrial Light and Magic (ILM) and Pixar, have three fundamental requirements for a sculpting system that can be used to design animate digital models, such as animated characters. Animators and artists want digital clayxe2x80x94a medium with the characteristics of real clay, (i.e., expressive in its ability to represent both smooth surfaces and very fine detail, intuitive to sculpt, easy to manipulate, responsive to user input) and the advantages of a digital media that include the ability to undo, script, duplicate, integrate into digital animation systems, and store permanently. The sculpting methods should be able to execute on standard computer hardware at interactive rates, and the system must fit into existing animation production pipelines. That is, the system must be able to read standard 3D representations or 3D scanned data from clay maquettes, and output models compatible with those pipelines.
The limitations of prior art data structures and modeling systems, and the needs of the animation industry have been partially addressed by the introduction of adaptively sampled distance fields (ADFs), as described by Frisken et al. in xe2x80x9cAdaptively Sampled Distance Fields: A General Representation of Shape for Computer Graphics,xe2x80x9d Proc. SIGGRAPH 2000, pp. 249-254, 2000.
There, ADFs are introduced, basic methods for generating, rendering, and sculpting ADFs are described, and a number of applications where ADFs can be used are listed. As an advantage, ADFs store only as much data as required to represent the detail in an object.
Classically, a distance field can be represented as distances, stored in a memory as scalar values. The distances specify minimum distances to surfaces of an object.
When the distances are signed, the sign can be used to distinguish between the inside and outside of the object. Zero distance values represent the surfaces.
An adaptively sample distance field (ADF) can be generated by adaptively sampling the object""s shape, and storing the sampled distance values in a spatial hierarchy for efficient processing.
Distances at arbitrary points in the ADF can then be reconstructed from the sampled values, and used for computerized processing such as rendering or sculpting. The use of adaptive sampling permits high sampling rates in regions of fine detail, and low sampling rates where the distance field varies smoothly. Thus, ADFs enable high accuracy without excessive memory requirements.
Frisken et al. discuss a basic sculpting procedure for ADFs and outline methods for generating and rendering ADFs. However, in many aspects, the prior art ADF manipulation methods are inadequate for a production system such as required by the animation industry.
Specifically, a bottom-up generation method requires too much memory and too many distance computations, while a top-down method requires time consuming searches for neighbor cells in an octree, and unnecessary repeated recomputation of distance values. Both approaches exhibit poor spatial and temporal memory coherence for cells and distance values. These memory and processing limitations place practical restrictions on the maximum number of ADF levels that can be generated.
To render ADFs, prior art ray casting methods are sufficiently fast for small local updates on a desktop Pentium class system. However, ray casting, as known, is too slow for local updates on low-end systems, such as embedded processors in hand-held devices, and woefully inadequate for camera or view changes such as panning, rotation, and zooming. In addition, the prior art ADF manipulation methods (1) do not address easy-to-use user interfaces for digital sculpting (2) do not provide efficient methods for converting ADFs to standard graphical representations, such as polygons (3) do not provide any methods for correcting distance values other than those at the object""s surfaces (4) do not support hardware acceleration, and (5) only discrete steps are supported during editing.
However, ADFs could still be an appropriate data structure for use with a quality sculpting system that meets the needs of digital studios if sufficient improvements could be provided. ADFs have a number of advantages for the entertainment industry. For example, ADFs integrate volumes and surfaces into a single representation, thereby potentially reducing the number of independent representations required by production systems. In addition, ADFs could be combined by simple constructive solid geometry (CSG) operations so that individual parts of a model can be separately modeled, and later joined together. This feature could decrease production costs during model design by maintaining libraries of model parts and features to quickly and easily design new models and characters.
One characteristic of surface-limited ADF generation is that interior and exterior ADF cells near the surface of the model may not accurately represent the distance field within those cells. For some applications, there is a need to identify and regenerate these interior and exterior ADF cells until the distance values in those cells substantially represent the distance field.
The present invention provides an innovative volumetric sculpting system that uses adaptively sampled distance fields (ADFs) to enable users to have better control while orienting and positioning sculpting tools relative to surfaces of digitized models. Distance values are used to constrain the sculpting tools, and control vertices are used for region-based conversion to triangles during editing of the model. In addition, the sculpted models are always without bothersome cracks and holes making them xe2x80x9cwatertight.xe2x80x9d
The invention also provides advanced model generating and editing methods that reduce memory requirements, provide better memory coherency, and reduced computational costs. Also provided are methods for correcting the entire distance field after multiple sculpting operations.
The invention also provides several new rendering approaches that take advantage of hardware acceleration in standard PCs, including fast generation of triangles and surface points. Methods for inputting and outputting models from the system include an improved method for generating ADFs from scanned range images, and a new and very fast method for generating topologically consistent triangle models from ADFs at various levels of detail (LOD).
The invention, as described herein, provides animation artists with an interactive system for sculpting. The system provides the ideal modeling media in the form of digital clay. The system and methods of the invention can represent very high resolution shapes at minimal memory costs, operate with standard computer hardware, and enable easy integration with existing animation production pipelines.
Although the sculpting system is designed to meet the demands of high-end production studios, the system also has applications in other areas of the entertainment industry, such as character design for games and virtual reality environments. The system can also be used for industrial modeling, particularly where the models cannot be generated parametrically. The ability to output variable level-of-detail models with low polygon counts, as required by these applications, enables easy integration of ADF-based models into existing polygon engines. In addition, the modeling methods of the invention can be used by low-end computing devices.
More particularly, the invention provides a method for modeling a graphics object. An adaptively sampled distance field is generated from a model according to an error measure. The adaptively sampled distance field includes interior, surface, and exterior cells. Each cell stores distance values, and the distance values of the surface cells always satisfy the error measure. A subset of cells are selected from the adaptively sampled distance field. The subset of cells only include interior and exterior cells. The selected cells are subdivided and the distance values for the subdivided cells are regenerated, until the distance values of the subdivided cells satisfy the error measure.